Artificial Intelligence Approaches for Energies
Gwanggil Jeon ()
Additional contact information
Gwanggil Jeon: Department of Embedded Systems Engineering, Incheon National University, 119 Academy-ro, Yeonsu-gu, Incheon 22012, Korea
Energies, 2022, vol. 15, issue 18, 1-3
Abstract:
In recent years, it has been noted that deep learning, machine learning, and artificial intelligence models are growing in popularity when applying big data for energy control and decision-making processes [...]
Keywords: n/a (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
https://www.mdpi.com/1996-1073/15/18/6651/pdf (application/pdf)
https://www.mdpi.com/1996-1073/15/18/6651/ (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:15:y:2022:i:18:p:6651-:d:912529
Access Statistics for this article
Energies is currently edited by Ms. Agatha Cao
More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().